6 citations · 7 across the 10 of their papers we have counts for
11 papers
DART: Decoded Attention over Recurrent States for Efficient Long-Context Sequence Modeling
Yixiao Qian, Song Chen, Pengkai Wang +3
Modern language models are built primarily from Transformers, recurrent models, and their hybrid architectures. Transformers rely on token-level attention memories, while recurrent…
A Continuous-Time Analysis of Smoothed Matrix-Polar Spectral Gradient Flows for Muon-Type Optimization
Jinlin Liu, Song Chen, Jiaxu Liu +1
This paper studies smoothed matrix-polar spectral gradient flows for unconstrained matrix-valued optimization.The canonical polar-factor map loses smoothness at rank-deficient matr…
DSSMs: State Space Models with Explicit Memory via Delay Differential Equations
Yixiao Qian, Song Chen, Jiaxu Liu +2
State Space Models (SSMs) have emerged as a powerful paradigm for efficient long-sequence modeling, offering parallel training and fast linear-time recurrent inference. However, li…
A Backstepping Framework for Unconstrained Accelerated Optimization Algorithms
Song Chen, Jiaxu Liu, Chao Xu
This paper introduces a control-theoretic perspective on unconstrained optimization algorithms using the backstepping methods. We model the optimization process as an augmented str…
Swarm-Inspired Generation of Collective Behaviors in Graph Dynamical Systems
Ji Chen, Song Chen, Chengzhang Gong +2
Collective behavior arises when locally interacting units produce coordinated global organization, from synchronization in dynamical systems to task-relevant information flow on gr…
Distributed physics-informed neural networks via domain decomposition for fast flow reconstruction
Yixiao Qian, Jiaxu Liu, Zewei Xia +3
Physics-Informed Neural Networks (PINNs) offer a powerful paradigm for flow reconstruction, seamlessly integrating sparse velocity measurements with the governing Navier-Stokes equ…
Accelerated Distributed Aggregative Optimization
Jiaxu Liu, Song Chen, Shengze Cai +2
This paper delves into the investigation of a distributed aggregative optimization problem within a network. In this scenario, each agent possesses its own local cost function, whi…
PiRD: Physics-informed Residual Diffusion for Flow Field Reconstruction
Siming Shan, Pengkai Wang, Song Chen +3
The use of machine learning in fluid dynamics is becoming more common to expedite the computation when solving forward and inverse problems of partial differential equations. Yet,…
Accelerated Distributed Aggregative Optimization
Jiaxu Liu, Song Chen, Shengze Cai +1
In this paper, we investigate a distributed aggregative optimization problem in a network, where each agent has its own local cost function which depends not only on the local stat…
The Novel Adaptive Fractional Order Gradient Decent Algorithms Design via Robust Control
Jiaxu Liu, Song Chen, Shengze Cai +1
The vanilla fractional order gradient descent may oscillatively converge to a region around the global minimum instead of converging to the exact minimum point, or even diverge, in…
Neural Observer with Lyapunov Stability Guarantee for Uncertain Nonlinear Systems
Song Chen, Shengze Cai, Tehuan Chen +2
In this paper, we propose a novel nonlinear observer based on neural networks, called neural observer, for observation tasks of linear time-invariant (LTI) systems and uncertain no…